713 citations · 805 across the 4 of their papers we have counts for
4 papers
VINNA for Neonates -- Orientation Independence through Latent Augmentations
Leonie Henschel, David Kügler, Lilla Zöllei +1
Fast and accurate segmentation of neonatal brain images is highly desired to better understand and detect changes during development and disease. Yet, the limited availability of g…
Identifying and Combating Bias in Segmentation Networks by leveraging multiple resolutions
Leonie Henschel, David Kügler, Derek S Andrews +2
Exploration of bias has significant impact on the transparency and applicability of deep learning pipelines in medical settings, yet is so far woefully understudied. In this paper,…
FastSurferVINN: Building Resolution-Independence into Deep Learning Segmentation Methods -- A Solution for HighRes Brain MRI
Leonie Henschel, David Kügler, Martin Reuter
Leading neuroimaging studies have pushed 3T MRI acquisition resolutions below 1.0 mm for improved structure definition and morphometry. Yet, only few, time-intensive automated imag…
FastSurfer -- A fast and accurate deep learning based neuroimaging pipeline
Leonie Henschel, Sailesh Conjeti, Santiago Estrada +3
Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large cohort studies with thousands o…